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Remove examples for the time being

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Andrew Brookins 2021-08-31 16:34:19 -07:00
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235
README.md
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@ -10,245 +10,14 @@ redis-developer-python includes an ORM/ODM.
### Declarative model classes ### Declarative model classes
```pyhon
import decimal
import datetime
from typing import Optional, List
import redis
from pydantic import ValidationError
from redis_developer.orm import (
RedisModel,
Field,
Relationship,
)
# Declarative model classes
class BaseRedisModel(RedisModel):
class Meta:
database = redis.Redis(password="my-password", decode_responses=True)
model_key_prefix = "redis-developer:"
class Address(BaseRedisModel):
address_line_1: str
address_line_2: Optional[str]
city: str
country: str
postal_code: str
class Order(BaseRedisModel):
total: decimal.Decimal
currency: str
created_on: datetime.datetime
class Member(BaseRedisModel):
first_name: str
last_name: str
email: str = Field(unique=True, index=True)
join_date: datetime.date
# Creates an embedded document: stored as hash fields or JSON document.
address: Address
# Creates a relationship to data in separate Hash or JSON documents.
orders: Optional[List[Order]] = Relationship(back_populates='member')
# Creates a self-relationship.
recommended_by: Optional['Member'] = Relationship(back_populates='recommended')
class Meta(BaseRedisModel.Meta):
model_key_prefix = "member"
primary_key_pattern = ""
# Validation
address = Address(
address_line_1="1 Main St.",
city="Happy Town",
state="WY",
postal_code=11111,
country="USA"
)
# Raises ValidationError: last_name, address are required
try:
Member(
first_name="Andrew",
zipcode="97086",
join_date=datetime.date.today()
)
except ValidationError as e:
pass
# Raises ValidationError: join_date is not a date
try:
Member(
first_name="Andrew",
last_name="Brookins",
join_date="yesterday"
)
except ValidationError as e:
pass
# Passes validation
member = Member(
first_name="Andrew",
last_name="Brookins",
email="a@example.com",
address=address,
join_date=datetime.date.today()
)
# Save a model instance to Redis
address.save()
address2 = Address.get(address.pk)
assert address2 == address
# Save a model with relationships (TODO!)
member.save()
# Save many model instances to Redis
today = datetime.date.today()
members = [
Member(
first_name="Andrew",
last_name="Brookins",
email="a@example.com",
address=address,
join_date=today
),
Member(
first_name="Kim",
last_name="Brookins",
email="k@example.com",
address=address,
join_date=today
)
]
Member.add(members)
# Get a model instance from Redis using the primary key.
member = Member.get(1)
# Update a model instance in Redis
member.first_name = "Brian"
member.last_name = "Sam-Bodden"
member.save()
# Or, with an implicit save:
member.update(first_name="Brian", last_name="Sam-Bodden")
# Or, affecting multiple model instances with an implicit save:
Member.filter(Member.last_name == "Brookins").update(last_name="Sam-Bodden")
# Exact-value queries on indexed fields
# What if the field wasn't unique and there were two "a@example.com"
# entries? This would raise a MultipleObjectsReturned error:
member = Member.get(Member.email == "a.m.brookins@gmail.com")
# What if you know there might be multiple results? Use filter():
members = Member.filter(Member.last_name == "Brookins")
# What if you want to only return values that don't match a query?
members = Member.exclude(Member.last_name == "Brookins")
# You can combine filer() and exclude():
members = Member.filter(Member.last_name == "Brookins").exclude(
Member.first_name == "Andrew")
```
### Serialization and validation based on model classes ### Serialization and validation based on model classes
### Save a model instance to Redis ### Save a model instance to Redis
### Get a single model instance from Redis ### Get a single model instance from Redis
### Update a model instance in Redis ### Update a model instance in Redis
### Batch/bulk insert and updates ### Batch/bulk insert and updates
### Declarative index creation and automatic index management
### Declarative “primary key” ### Declarative “primary key”
### Declarative relationships (via Sorted Sets) or Embedded documents (JSON) ### Embedded models (JSON)
### Exact-value queries on indexed fields ### Exact-value queries on indexed fields
### Declarative index creation and automatic index management (RediSearch)
### Ad-hoc numeric range and full-text queries (RediSearch) ### Ad-hoc numeric range and full-text queries (RediSearch)
### Aggregations (RediSearch) ### Aggregations (RediSearch)
### Unanswered Questions
What's the difference between these two forms?
```python
from redis_developer.orm import (
RedisModel,
indexed,
unique
)
class Member(RedisModel):
email: unique(str)
email: indexed(str)
# email: Indexed[str] <- Probably not possible?
# email: IndexedStr <- This is how constrained types work in Pydantic
class Meta:
primary_key = "id"
indexes = ["email"] # <- How about this?
```
It appears that Pydantic uses functions when declaring the type requires some
kind of parameter. E.g., the max and min values for a constrained numeric
field.
Indexing probably requires, in some cases, parameters... so it should be a
function, probably. And in general, function vs. class appears to be only a case
of whether parameters are required.
1. unique() and indexed() require lots of work.
2. IndexedStr - what does that even mean exactly?
3. indexes = [] - Here, we could hook into class-level validation and add logic
to make sure that any indexed values were unique. Right?
### Unique checking
When is the right time to check if e.g. an email field is unique in Redis?
If we check on instantiation of the model, we'll still need to check again when
we save the model.
### Field() vs constrained int, etc.
Pydantic includes field helpers like constr, etc. that apply a schema to values.
On top of that, we'll have a Field() helper that includes options common to all
data types possible for a field.
This is where we'll track if we should index a field, verify uniqueness, etc.
But for facts like numeric constraints, we'll rely on Pydantic.
### Automatic fields
Redis doesn't have server-side automatic values, dates, etc. So we don't need to
worry about refreshing from the server to get the automatically-created values.
As soon as someone saves a model, we, the ORM, will have created the automatic
values, so we can just set them in the model instance.

165
test.py
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@ -1,165 +0,0 @@
import decimal
import datetime
from typing import Optional, List
import redis
from pydantic import ValidationError
from redis_developer.orm import (
RedisModel,
Field,
Relationship,
)
# Declarative model classes
class BaseRedisModel(RedisModel):
class Meta:
database = redis.Redis(password="my-password", decode_responses=True)
global_key_prefix = "redis-developer:"
class Address(BaseRedisModel):
address_line_1: str
address_line_2: Optional[str]
city: str
country: str
postal_code: str
class Order(BaseRedisModel):
total: decimal.Decimal
currency: str
created_on: datetime.datetime
class Member(BaseRedisModel):
first_name: str
last_name: str
email: str = Field(unique=True, index=True)
join_date: datetime.date
# Creates an embedded document: stored as hash fields or JSON document.
address: Address
# Creates a relationship to data in separate Hash or JSON documents.
orders: Optional[List[Order]] = Relationship(back_populates='member')
# Creates a self-relationship.
recommended_by: Optional['Member'] = Relationship(back_populates='recommended')
class Meta(BaseRedisModel.Meta):
model_key_prefix = "member"
primary_key_pattern = ""
# Validation
address = Address(
address_line_1="1 Main St.",
city="Happy Town",
state="WY",
postal_code=11111,
country="USA"
)
# Raises ValidationError: last_name, address are required
try:
Member(
first_name="Andrew",
zipcode="97086",
join_date=datetime.date.today()
)
except ValidationError as e:
pass
# Raises ValidationError: join_date is not a date
try:
Member(
first_name="Andrew",
last_name="Brookins",
join_date="yesterday"
)
except ValidationError as e:
pass
# Passes validation
member = Member(
first_name="Andrew",
last_name="Brookins",
email="a@example.com",
address=address,
join_date=datetime.date.today()
)
exit()
# Save a model instance to Redis
address.save()
address2 = Address.get(address.pk)
assert address2 == address
exit()
# Save a model with relationships (TODO!)
member.save()
# Save many model instances to Redis
today = datetime.date.today()
members = [
Member(
first_name="Andrew",
last_name="Brookins",
email="a@example.com",
address=address,
join_date=today
),
Member(
first_name="Kim",
last_name="Brookins",
email="k@example.com",
address=address,
join_date=today
)
]
Member.add(members)
# Get a model instance from Redis using the primary key.
member = Member.get(1)
# Update a model instance in Redis
member.first_name = "Brian"
member.last_name = "Sam-Bodden"
member.save()
# Or, with an implicit save:
member.update(first_name="Brian", last_name="Sam-Bodden")
# Or, affecting multiple model instances with an implicit save:
Member.filter(Member.last_name == "Brookins").update(last_name="Sam-Bodden")
# Exact-value queries on indexed fields
# What if the field wasn't unique and there were two "a@example.com"
# entries? This would raise a MultipleObjectsReturned error:
member = Member.get(Member.email == "a.m.brookins@gmail.com")
# What if you know there might be multiple results? Use filter():
members = Member.filter(Member.last_name == "Brookins")
# What if you want to only return values that don't match a query?
members = Member.exclude(Member.last_name == "Brookins")
# You can combine filer() and exclude():
members = Member.filter(Member.last_name == "Brookins").exclude(
Member.first_name == "Andrew")